Similarity Function With Temporal Factor In Collaborative Filtering: Data Mining - Tapa blanda

Khatri, Meghna; Rana, Chhavi

 
9783659179952: Similarity Function With Temporal Factor In Collaborative Filtering: Data Mining
Tapa blanda
ISBN 10: 3659179957 ISBN 13: 9783659179952
Editorial: LAP LAMBERT Academic Publishing, 2012

Sinopsis

Similarity function is the key to accuracy of collaborative filtering algorithms. Adding a time factor to it addresses the problem of handling the web data efficiently as it is highly dynamic in nature. The data used in collaborative filtering algorithms is collected over as long period of time, in the form of feedbacks, clicks, etc. The interest of user or popularity of an item tends to change as new seasons, moods or festivals. The similarity function with temporal factor can efficiently handle the dynamics of web data as it captures and assigns weightage to the data. More recent data is given more weightage when similarity is calculated. in this way, the recent trends and older and obsolete data values are discarded when new unobserved items are predicted using collaborative filtering algorithms. Hence, better results and more accuracy.

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Reseña del editor

Similarity function is the key to accuracy of collaborative filtering algorithms. Adding a time factor to it addresses the problem of handling the web data efficiently as it is highly dynamic in nature. The data used in collaborative filtering algorithms is collected over as long period of time, in the form of feedbacks, clicks, etc. The interest of user or popularity of an item tends to change as new seasons, moods or festivals. The similarity function with temporal factor can efficiently handle the dynamics of web data as it captures and assigns weightage to the data. More recent data is given more weightage when similarity is calculated. in this way, the recent trends and older and obsolete data values are discarded when new unobserved items are predicted using collaborative filtering algorithms. Hence, better results and more accuracy.

Biografía del autor

Meghna Khatri has obtained her Master's degree in Computer Science Engineering from Maharishi Dayanand University. Her main focus of research is collaborative filtering.She has several publications in international and national journals.Apart from academics, she has been an active participant in co-curricular activities at school and college level.

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Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2012
Idioma
Inglés
ISBN 10 
3659179957
ISBN 13 
9783659179952
Encuadernación
Tapa blanda
Número de páginas
56
Contacto del fabricante
no disponible
Persona responsable
no disponible